Published September 2, 2022 | Version 1.0

Container spreader pose tracking dataset

  • 1. Foundation for Research and Technology – Hellas (FORTH)

Description

This dataset contains image sequences that feature a moving quay crane spreader in a port environment while unloading a container cargo vessel. A container crane spreader is a device that is installed on a crane and used to lift containers after attaching onto them.


The sequences were acquired from a viewpoint similar to that of the crane operator using a camera installed next to the operator’s cabin at a height of approximately 20 meters above the quay. The camera thus moves with the crane, resulting in a non-stationary image background.

The dataset is organized into several RAR archives, one for each sequence. In addition to the undistorted image frames, it includes for every sequence a text file whose each line consists of the frame id for every image, the spreader’s bounding box and the spreader’s 6D pose (Rodrigues vector for the orientation, and the translation vector). The axis-aligned 2D bounding box is in the format x0 y0 w h where (x0, y0) is the top left corner and w x h its size, all in pixels. The spreader’s pose is defined with respect to the camera coordinate frame. Also included are the camera intrinsics matrix K for each sequence along with a common 3D mesh model for the spreader.

The spreader’s mesh model is supplied in PLY format. For a certain image frame, a model vertex M transforms to the camera coordinate system as R*M + t, R and t being the spreader’s pose (R is the equivalent rotation matrix). The homogeneous coordinates of that vertex’s projection on the image frame are K*(R*M + t).


The dataset can support research on topics such as object localization, object detection, pose estimation, tracking, etc.
If you use this dataset in your research work, you are kindly asked to cite the following paper in your publications:

M. Lourakis and M. Pateraki, "Markerless Visual Tracking of a Container Crane Spreader," 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021, pp. 2579-2586, doi: 10.1109/ICCVW54120.2021.00291.

Notes

The sequences have been acquired by two different PtGrey color GigE cameras, FL3-GE-28S4C-C and BFLY-PGE-31S4C-C. The frames of each sequence are in a separate RAR archive. The spreader 3D model is in spreader40ft.ply.

Files

Files (25.3 GB)

Name Size
md5:8b90ee44f002f0a60e2a0727f7be14ab
5.2 GB Download
md5:975ccfafba83a0ec24f413d1da5ef3bf
2.2 GB Download
md5:a57ae0d0e4cdbb61c13b741e99ca4634
2.0 GB Download
md5:0ca17afb718d64d250c98432d902384e
4.7 GB Download
md5:3233efc9517e8ab313412d1b3b4d00cb
3.8 GB Download
md5:d8f692463da448f90a6d79513ab722c5
2.3 GB Download
md5:5abfe9e7a075a18e6654ef96452d900e
2.7 GB Download
md5:c4f91cd4e7c78ced4f5cca769bbc8f81
2.4 GB Download
md5:16567b8b9970ca270ff6255fb5ef2652
13.6 kB Download

Additional details

Funding

European Commission
sustAGE - Smart environments for person-centered sustainable work and well-being 826506